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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Magnetic Energy Dissipation and γ-Ray Emission in Energetic Pulsars

Abstract Some of the most energetic pulsars exhibit rotation-modulated γ -ray emission in the 0.1–100 GeV band. The luminosity of this emission is typically 0.1%–10% of the pulsar spin-down power ( γ -ray efficiency), implying that a significant fraction of the available electromagnetic energy is dissipated in the magnetosphere and reradiated as high-energy photons. To investigate this phenomenon we model a pulsar magnetosphere using 3D particle-in-cell simulations with strong synchrotron cooling. We particularly focus on the dynamics of the equatorial current sheet where magnetic reconnection and energy dissipation take place. Our simulations demonstrate that a fraction of the spin-down power dissipated in the magnetospheric current sheet is controlled by the rate of magnetic reconnection at microphysical plasma scales and only depends on the pulsar inclination angle. We demonstrate that the maximum energy and the distribution function of accelerated pairs is controlled by the available magnetic energy per particle near the current sheet, the magnetization parameter. The shape and the extent of the plasma distribution is imprinted in the observed synchrotron emission, in particular, in the peak and the cutoff of the observed spectrum. We study how the strength of synchrotron cooling affects the observed variety of spectral shapes. Our conclusions naturally explain why pulsars with higher spin-down power have wider spectral shapes and, as a result, lower γ -ray efficiency.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗
DOE OSTI2023

Distributed Power Allocation for 6-GHz Unlicensed Spectrum Sharing via Multi-agent Deep Reinforcement Learning

We consider the problem of power allocation over the 6 GHz Unlicensed National Information Infrastructure (UNII)- 5 spectrum. We propose a novel deep Reinforcement Learning (DRL)-based distributed power allocation scheme which utilizes the multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm. In particular, we model the base stations (BSs) as DRL agents that simultaneously determine the transmit powers to their scheduled user equipment (UE) in a synchronized manner. The power decision of each BS is based on its own observation of the radio environment, which consists of several local interference measurements and a limited amount of information obtained from other BSs. One advantage of the proposed scheme is that it addresses the single-agent non-stationarity problem of RL in the multi-agent scenario by incorporating the actions and observations of other BSs into each BS’s own critic which helps it to gain a more accurate perception of the overall radio environment. A centralized-training-distributed execution framework is used to train the policies where the critics are trained over the joint actions and observations of all BSs while the actor of each BS only takes the local observation as input in order to produce the transmit power. Simulation shows that the proposed power allocation scheme can achieve better throughput performance than several state-of-the-art approaches.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Retractable Sensor for Reactor Experiments

This presentation is to orient a mechanical or nuclear engineering senior design team so that they can help solve an instrumentation problem found in high power test reactors. Test reactors such as the Advanced Test Reactor (ATR) at the Idaho National Laboratory are used to irradiate nuclear fuels and materials to evaluate performance after high levels of exposure to a reactor in-pile environment. The purpose of the experiments is to determine property changes as the materials or fuels are bombarded with fast neutrons (and thermal (slow) neutrons as well). Typically, the irradiation must take place at a very specific temperature. Sometimes other parameters are monitored as well as properties such as creep, or gas composition, etc. However, the fast neutrons cause changes in not only the materials, but also in the transducers that are placed in the neutron flux, e.g., thermocouples or optical fibers. This task will be limited to considering temperature measurements. Thermocouples experience decalibration from not only the neutron flux, but also from the very high temperatures that are sometimes measured. Optical fibers darken in a neutron or gamma flux. However, it takes quite a few hours, or days for these changes to manifest. High power test reactors typically run at a constant power and so the temperature in an experiment is fairly stable over time. Because the changes are typically very slow, even a single temperature measurement per day, would provide 95% of a perfect data set. The basic concept of this effort is to push a very small diameter thermocouple or optical fiber into the location to be measured, leave it for 30 seconds or so for it to come to equilibrium, and transmit the signal, and then pull it up and away from the high neutron flux and high temperature region. The distance the thermocouple or fiber would need to move is on the order of 50 – 100 cm. By doing this, the thermocouple junction or optical fiber would spend only a few hours in the high flux/high temperature environment over the life of the irradiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Lightning radiometry in visible and infrared bands

Calibrated measurements of lightning optical emissions are critical for both quantifying the impacts of lightning in our atmosphere and devising detection instruments with sufficient dynamic range capable of yielding close to 100% detection efficiency. However, to date, there is only a limited number of investigations that have attempted to take such calibrated measurements. Here, in this work, we report the power radiated by lightning in both visible and infrared bands, assuming isotropic emission, and accounting for atmospheric absorption. More precisely, we report peak radiated power and total radiated energy in the combined visible plus near-infrared range (VNIR, 0.34–1.1 μm), around the H α line (652–667 nm), and for the 2–2.5 μm infrared band. The estimated peak power and total energy radiated by negative cloud-to-ground return strokes in the VNIR range is 130 MW and 20 kJ, respectively. Additionally, we detected peak radiated powers of 12 and 0.19 MW in the H α and infrared bands, respectively. We cross-reference the optical data set with peak current reported by a lightning detection network. The resulting trend is that optical power emitted around the H α line scales with peak return stroke current according to a power law with exponent equal to 1.25. This trend, which should be approximately true across the entire visible spectrum, can be attributed to the plasma negative differential resistance of the lightning return stroke channel. We conclude by discussing the challenges in performing calibrated measurements of lightning optical power in different bands and comparing the results with previously-collected data with different experimental setups, observation conditions, and calibration methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Search for very-short-baseline oscillations of reactor antineutrinos with the SoLid detector

In this paper we report the first scientific result based on antineutrinos emitted from the BR2 reactor at SCK CEN. The SoLid experiment uses a novel type of highly granular detector whose basic detection unit combines two scintillators, polyvinyl toluene (PVT) and Li 6 F : ZnS ( Ag ) , to measure antineutrinos via their inverse- β -decay products. An advantage of PVT is its highly linear response as a function of deposited particle energy. The full-scale detector comprises 12 800 voxels and operates over a very short 6.3–8.9 m baseline from the reactor core. The detector segmentation and its three-dimensional imaging capabilities facilitate the extraction of the positron energy from the rest of the visible energy, allowing the latter to be utilized for signal-background discrimination. We present a result obtained from 280 reactor-on days (55 MW mean power) and 172 reactor-off days, respectively, of live data taking. A total of 29 479 ± 603 (stat) antineutrino candidates have been selected, corresponding to an average rate of 105 events per day and a signal-to-background ratio of 0.27. A search for disappearance of antineutrinos to a sterile state has been conducted using complementary model-dependent frequentist and Bayesian fits, providing constraints on the allowed region of the reactor antineutrino anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Fast and Accurate Greenberger-Horne-Zeilinger Encoding Using All-to-All Interactions

The 𝑁-qubit Greenberger-Horne-Zeilinger (GHZ) state is an important resource for quantum technologies. Here, we consider the task of GHZ encoding using all-to-all interactions, which prepares the GHZ state in a special case, and is furthermore useful for quantum error correction, interaction-rate enhancement, and transmitting information using power-law interactions. The naive protocol based on parallelizing CNOT gates takes O(1)-time of Hamiltonian evolution. In this work, we propose a fast protocol that achieves GHZ encoding with high accuracy. The evolution time O⁡(log 2 ⁡𝑁/𝑁) almost saturates the theoretical limit Ω⁡(log⁡𝑁/𝑁). Moreover, the final state is close to the ideal encoded one with high fidelity >1–10 −3 , up to large system sizes 𝑁 ≲ 2000. The protocol only requires a few stages of time-independent Hamiltonian evolution; the key idea is to use the data qubit as control, and to use fast spin-squeezing dynamics generated by e.g., two-axis twisting.

quantum computation↗
DOE OSTI2024

Concepts for Neutrino Applications

Will neutrinos find uses outside basic science? It may be too early to say, but neutrino physicists have already imagined a variety of possibilities from the relatively modest to the more blue-sky. In this review, we survey the range of proposed applications, most involving nuclear reactors and other fission sources. We give special attention to the most recent proposals, including verifying submarine reactor integrity, safeguarding advanced nuclear power plants, and monitoring spent nuclear fuel. All of these concepts take advantage of the fact that neutrinos pass through barriers other signals cannot penetrate. That same fact creates the central challenge for neutrino applications: the size and complexity of detectors needed to collect a signal. Although the weakly interacting nature of neutrinos makes them fundamentally difficult to use, developments in detector technology are making some ideas more feasible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

WBG-Enabled Current-Source Inverters for Integrated PM Motor Drives

This project takes advantage of the special capabilities of wide-bandgap (WBG) power semiconductor devices to develop innovative power electronics in the form of new current-source inverters (CSIs) that offer promising advantages over the dominant voltage-source inverter (VSI) topology. These CSIs, in turn, are extremely well-suited for integration into the housings of permanent magnet synchronous machines (PMSMs) to form integrated motor drives (IMDs). These new IMDs offer great promise for achieving major energy savings in a wide variety of applications that benefit from adjustable-speed control, including air conditioners, laundry appliances, industrial pumps/compressors, electric vehicles, and aerospace drives. WBG devices play a critical enabling role in these new IMDs because of their transformative features including much higher switching frequencies, lower losses, and compatibility with high operating temperatures. When incorporated into new CSI-based IMDs with PM machines, these WBG switches open the door to achieving major increases in power density, drive system efficiency, and fault tolerance, as well as substantial reductions in electromagnetic interference (EMI), manufacturing cost, and temperature-induced failures. The higher operating temperature capability of WBG devices compared to conventional silicon power devices is very appealing in IMD applications because the power electronics is mounted in close proximity to the motors which typically operate at temperatures well above the maximum limits of today’s silicon-based power electronics. This project has succeeded in designing, building, and testing multiple prototype versions of this CSI-IMD that have overcome many technical challenges in order to demonstrate the impressive performance improvements that can be achieved by the WBG-enabled CSI-IMD. The preliminary demo and bench-top versions of the current-source inverter developed during the first two years of the project were critical to laying the technical foundations for the 3 kW prototype CSI-IMD unit that was successfully built and tested during the third year. This prototype CSI-IMD unit was designed to fit within the housing envelope of the original permanent magnet (PM) synchronous machine in order to meet the demanding power density requirements that were set at the beginning of the project. All of the remaining performance objectives set for the prototype CSI-IMD unit including efficiency and electromagnetic interference (EMI) were also met. The last 18 months of the project were devoted to developing further enhancements of the WBG-enabled CSI-IMD technology that better prepare it for commercial production. More specifically, an upgraded version of the prototype CSI-IMD unit was developed that moved the power electronics into the same machine housing chamber as the motor, substantially raising the thermal demands on the power electronics. Tests with five different combinations of motor enclosure types and air cooling configurations were evaluated. Importantly, this work confirmed that the power electronics can deliver its full rated power and still operate well within its maximum temperature limits even for worst-case conditions when the housing is “totally-enclosed” without any openings for air to enter or exit the enclosure, and no blower/fan is provided to blow air over the outside surface of the enclosure. Reaching the full performance and energy-savings potential of this disruptive CSI-IMD motor drive technology is highly consistent with ARPA-E’s stated mission to “enhance the economic and energy security of the United States” while also supporting its commitment to “ensure that the U.S. maintains a technological lead in developing and deploying advanced energy technologies”. Follow-on projects are under way to explore the scalability of WBG-enabled CSI-IMD technology to 100 kW (peak) electric vehicle traction drives and fault-tolerant modular motor drives for future electrified aircraft propulsion applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Robust Statistical Approach for Determination of Graphite Nitridation Using Bayesian Model Comparison

A better estimation of surface reaction efficiency of semiconductor-grade graphite with atomic nitrogen, as well as the calibration error are calculated using Bayesian updating based on experimental data. Compared with a conventional deterministic model, the stochastic model approach is a powerful tool in the sense that the model is capable of taking into account underlying error correlations among the data quantities. In this paper, we investigate four different stochastic models (called “stochastic system model classes” herein) corresponding to different descriptions of modeling and measurement error structures, given one deterministic physical model. These stochastic system model classes differ in the covariance matrix structure that is used in the uncertainty model to represent uncertainties associated with the physical model and experimental measurements. For each model class, Bayesian inference is used to estimate the posterior probabilities of the physical model parameters as well as of the stochastic model parameters. Model comparison and selection are then applied based on two measures including Bayesian evidence and Bayesian information criterion, as well as the deviance information criterion. Both measures suggest the stochastic model class, which considers that a correlation between errors in two data quantities among different data points is the most plausible. With the stochastic model class, the range of uncertainty in surface reaction efficiency is estimated to be about two orders of magnitude at [Formula: see text].

Engineering↗
DOE OSTI2023

Comparison of the Core-collapse Evolution of Two Nearly Equal-mass Progenitors

Abstract We compare the core-collapse evolution of a pair of 15.8 M ☉ stars with significantly different internal structures, a consequence of the bimodal variability exhibited by massive stars during their late evolutionary stages. The 15.78 and 15.79 M ☉ progenitors have core masses (masses interior to an entropy of 4 k B baryon −1 ) of 1.47 and 1.78 M ☉ and compactness parameters ξ 1.75 of 0.302 and 0.604, respectively. The core-collapse simulations are carried out in 2D to nearly 3 s postbounce and show substantial differences in the times of shock revival and explosion energies. The 15.78 M ☉ model begins exploding promptly at 120 ms postbounce when a strong density decrement at the Si–Si/O shell interface, not present in the 15.79 M ☉ progenitor, encounters the stalled shock. The 15.79 M ☉ model takes 100 ms longer to explode but ultimately produces a more powerful explosion. Both the larger mass accretion rate and the more massive core of the 15.79 M ☉ model during the first 0.8 s postbounce time result in larger ν e / ν ¯ e luminosities and RMS energies along with a flatter and higher-density heating region. The more-energetic explosion of the 15.79 M ☉ model resulted in the ejection of twice as much 56 Ni. Most of the ejecta in both models are moderately proton rich, though counterintuitively the highest electron fraction ( Y e = 0.61) ejecta in either model are in the less-energetic 15.78 M ☉ model, while the lowest electron fraction ( Y e = 0.45) ejecta in either model are in the 15.79 M ☉ model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Probabilistic Power Consumption Modeling for Commercial Buildings Using Logistic Regression Markov Chain

The total energy consumed by buildings takes up to 40% of U.S. energy use, in which a large portion is contributed by commercial buildings. Building performance optimization is desirable but requires accurate building models with uncertainties taken into account. This paper proposes a novel probabilistic modeling method using Logistic Regression Markov Chain (LRMC). The LRMC model enhances the performance of traditional Markov Chain (MC) models by adopting time-variant transition matrices calibrated using logistic regression with exogenous inputs. Compared with existing building models, the proposed model produces accurate multi-step modeling results with full probability distribution. The proposed probabilistic building model is tested using actual commercial building measurements and modeling performance is evaluated with two probabilisitc metrics. The results show that the LRMC model has higher accuracy than traditional MC model and Logistic Regression (LR) model in that it yields lower error scores under both evaluation metrics.

Building modeling↗
DOE OSTI2021

Performance and cost of fuel cells for urban air mobility

Several companies are developing enabling elements of urban air mobility (UAM) for air taxis, including prototypes of electric vertical take-off and landing (eVTOL) vehicles. These prototypes incorporate electric and hybrid powertrains for multi-rotor and tilt-rotor crafts. Many eVTOLS are using batteries for propulsion and charging them rapidly between the flights or swapping them for slow charging overnight. Rapid charging degrades the battery cycle life while swapping requires multiple batteries and charging stations. This study has conducted a technoeconomic evaluation of the eVTOL air taxis with alternate powertrains using hydrogen fuel cell systems being developed for light-duty and heavy-duty vehicles. We consider performance metrics such as fuel cell engine power, weight, and durability; hydrogen consumption and weight of storage system; and maximum take-off weight. The metrics for economic evaluation are capital cost, operating and maintenance cost, fuel cost, and the total cost of ownership (TCO). In this work, we compare the performance and TCO of battery, fuel cell and fuel cell – battery hybrid powertrains for multi-rotor and tilt-rotor crafts. We show that fuel cells are the only viable concept for powering multi-rotor eVTOLs on an urban scenario that requires 60-mile range, and hybrid fuel cells are superior to batteries as powertrains for tiltrotor eVTOLs

08 HYDROGEN↗
DOE OSTI2021

Key Findings from LA100

This document describes high-level findings from the Los Angeles 100% Renewable Energy Study (LA100), a partnership between the Los Angeles Department of Water and Power (LADWP) and the National Renewable Energy Laboratory (NREL) to analyze potential pathways LA can take to achieve a 100% clean energy future. This is an excerpt of the LA100 Executive Summary (NREL/TP-6A20-79444-ES), which provides additional background and detail.

100% renewable energy↗
DOE OSTI2020

Calculating the angle between jet axes

We study the angle between i) the standard jet axis, ii) the axis of a jet which has been groomed using soft drop, with reduced sensitivity to soft radiation, iii) the jet axis obtained with the winner-take-all recombination scheme, which is insensitive to soft radiation at leading power. We calculate the distributions for these angles at next- to-leading logarithmic accuracy, including non-global logarithms. The angle between the standard and groomed jet axis directly probes soft wide-angle radiation, leading to a novel factorization formula. This angle is also very sensitive to nonperturbative physics, which is directly connected to nonperturbative contribution to the rapidity anomalous dimension for transverse momentum distributions. Comparing our predictions to Pythia we find good agreement, and we foresee applications to jet substructure in proton-proton and heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Enhancements to the New TREAT Automatic Reactor Control System (ARCS)

The Transient Reactor Test (TREAT) facility recently replaced the automatic reactor control system (ARCS). Here, this paper discusses some of the enhancements that were made during the ARCS replacement such as calculations to take into account the nonadiabatic effects and increasing the dynamic range for power and period indication. This paper also discusses upgrades that had been planned but were unable to implemented and potential upgrades for the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

High-Energy Density Capacitors for Electric Vehicle Traction Inverters

DC bus capacitors take up substantial space in a traction inverter, limiting the traction drive power density. Thus, several commercial capacitor technologies, under consideration for use as DC bus capacitors for electric vehicle traction inverters, were reviewed for their ability to optimize the volume of traction inverters and are evaluated in this paper. Three promising capacitor technologies--film, ceramic, and PLZT have been selected for detailed experimental characterization. Experimental results for equivalent series resistance, equivalent series inductance, and effective capacitance with respect to DC bias voltage for various operating frequencies and temperatures are presented. The results reveal the superiority of the PLZT capacitor in terms of power density, current conduction capability, and redundancy.

Chowdhury, Shajjad↗
DOE OSTI2024

Study of eVTOL Charging Impact on Airport Electrical Grids

Growth in commercial air traffic has increased the aviation industry's contribution to global emissions. Aircraft electrification can reduce greenhouse gas emissions along with being efficient and reliable. Advanced air mobility introduces the idea of an advanced and more efficient air transportation system. Electric and hybrid aircraft designs, such as electric vertical takeoff and landing (eVTOL), are being considered for a number of applications, such as urban air mobility, cargo delivery, and medical emergencies. Although the electrification of aircraft provides environmental benefits, their charging needs will place significant demand on the electrical grid. This work presents a grid impact study and infrastructure upgrade requirements analysis of eVTOL charging on a realistic distribution grid through power flow simulation analysis. The case study results show that the eVTOL charging can lead to power quality issues, such as undervoltage and equipment capacity overloading. Grid infrastructure, such as lines and transformers, would need to be upgraded, and voltage management strategies would need to be deployed to accommodate eVTOL charging at an existing airport.

advanced air mobility (AAM)↗